Method and system for evaluating acceleration factor influencing aging of lithium ion battery

Abstract

The invention relates to a method and system for evaluating acceleration factors influencing lithium ion battery aging, and the method comprises the steps: carrying out the parameter setting of a plurality of acceleration factors, and obtaining the test conditions of different acceleration factor combinations; under the test condition, performing an aging test on the lithium ion battery and performing real-time monitoring to obtain a battery aging process data set; and performing multi-factor analysis on the battery aging process data set to obtain influence degree evaluation results of different acceleration factors on the battery aging rate. According to the method, multiple acceleration factors are considered, and the comprehensiveness and accuracy of the battery aging test are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of battery performance testing, and particularly to a method and system for evaluating acceleration factors affecting the aging of lithium-ion batteries. Background Art

[0002] As a key component of modern electronic devices and new energy vehicles, the performance and lifespan of lithium-ion batteries are directly related to the overall quality of products and the user experience. Accelerated aging testing is an important means to evaluate the lifespan and reliability of batteries. However, traditional testing methods often only focus on a single acceleration factor, such as temperature or charge-discharge current, while ignoring the combined effects of different acceleration factors on the aging process.

[0003] Therefore, there is an urgent need in this field for a testing method that comprehensively considers multiple acceleration factors and accurately evaluates the degree of influence of acceleration factors on the accelerated aging process of batteries. Summary of the Invention

[0004] The present invention provides a method and system for evaluating acceleration factors affecting the aging of lithium-ion batteries to solve the deficiencies of the prior art.

[0005] The present invention provides a method for evaluating acceleration factors affecting the aging of lithium-ion batteries, including:

[0006] S1: Set parameters for multiple acceleration factors to obtain test conditions for different combinations of acceleration factors;

[0007] S2: Under the test conditions, conduct aging tests on lithium-ion batteries and monitor them in real time to obtain a dataset of the battery aging process;

[0008] S3: Conduct multi-factor analysis on the dataset of the battery aging process to obtain an evaluation result of the degree of influence of different acceleration factors on the battery aging rate.

[0009] By setting parameters and conducting combined tests on multiple acceleration factors, the present invention can comprehensively evaluate the degree of influence of different factors on the aging rate of lithium-ion batteries, avoiding the limitations of traditional single-factor tests. Secondly, the present invention uses real-time monitoring to obtain battery aging process data and combines multi-factor analysis technology to accurately quantify the contribution weights of each acceleration factor, providing a scientific basis for the accelerated life test of lithium-ion batteries. This not only improves the accuracy of battery life prediction but also guides battery design and optimization of the use environment, effectively extending the battery service life. At the same time, the present invention can significantly shorten the battery life evaluation cycle, reduce test costs, and provide more reliable product quality assurance for end users.

[0010] According to the method for evaluating acceleration factors affecting the aging of lithium-ion batteries provided by the present invention, the acceleration factors in step S1 include: temperature, charge-discharge rate, and SOC range.

[0011] According to an acceleration factor evaluation method for affecting the aging of lithium-ion batteries provided by the present invention, the combination methods of the different acceleration factor combinations in step S1 include:

[0012] Single-factor combination, the single-factor combination includes a temperature single factor, a charge-discharge rate single factor, and an SOC interval single factor;

[0013] Two-factor combination, the two-factor combination includes a combination of temperature and charge-discharge rate, a combination of temperature and SOC interval, and a combination of charge-discharge rate and SOC interval;

[0014] Three-factor combination, the three-factor combination is a combination of temperature, charge-discharge rate, and SOC interval.

[0015] According to an acceleration factor evaluation method for affecting the aging of lithium-ion batteries provided by the present invention, step S2 further includes:

[0016] S21: Under the test conditions, perform an aging test on the lithium-ion battery to obtain a battery performance parameter data set;

[0017] S22: Perform noise filtering and outlier processing on the battery performance parameter data set to obtain a battery aging process data set.

[0018] According to an acceleration factor evaluation method for affecting the aging of lithium-ion batteries provided by the present invention, step S21 specifically includes:

[0019] Perform high-frequency sampling processing on the terminal voltage of the battery during charge and discharge to obtain voltage change curve data;

[0020] Perform continuous recording processing on the current value of the battery during charge and discharge to obtain current change curve data;

[0021] Perform regular detection processing on the internal resistance change of the battery during cycling to obtain internal resistance growth trend data.

[0022] According to an acceleration factor evaluation method for affecting the aging of lithium-ion batteries provided by the present invention, step S2 further includes:

[0023] S23: Real-time monitor the safety state of the lithium-ion battery during the accelerated aging test process.

[0024] According to an acceleration factor evaluation method for affecting the aging of lithium-ion batteries provided by the present invention, step S23 specifically includes:

[0025] Continuously monitor the surface temperature of the battery through a temperature anomaly detector to obtain a battery temperature anomaly warning signal;

[0026] The battery terminal voltage is compared with upper and lower limits by a voltage anomaly detector to obtain a voltage overlimit warning signal;

[0027] The gas components in the environment around the battery are analyzed in real time by a gas sensor to obtain a battery leakage or bulging warning signal;

[0028] The battery temperature anomaly warning signal, the voltage overlimit warning signal, and the battery leakage or bulging warning signal are comprehensively judged and processed by a safety linkage control system to obtain a safety guarantee plan, and the safety guarantee plan includes test emergency interruption and degraded operation.

[0029] According to an accelerated factor evaluation method for affecting the aging of lithium-ion batteries provided by the present invention, step S3 specifically includes:

[0030] Calculate the time used for the battery to cycle the same number of weeks to obtain an aging rate index in the time dimension;

[0031] Count the number of cycles completed by the battery in the same time to obtain an aging rate index in the cycle dimension;

[0032] Calculate the number of cycles required for the battery to cycle to the same SOH value to obtain an aging rate index in the health state dimension;

[0033] Weigh the aging rate index in the time dimension, the aging rate index in the cycle dimension, and the aging rate index in the health state dimension to obtain a comprehensive influence degree score for different accelerated factor combinations, and use the comprehensive influence degree score of different accelerated factor combinations as the evaluation result of the influence degree of different accelerated factors on the battery aging rate and output it.

[0034] The present invention also provides an accelerated factor evaluation system for affecting the aging of lithium-ion batteries, including:

[0035] A parameter setting module: used to set parameters for a variety of accelerated factors to obtain test conditions for different accelerated factor combinations;

[0036] A test monitoring module: used to conduct an aging test on a lithium-ion battery under the test conditions, and also used to monitor the aging test process in real time to obtain a battery aging process data set;

[0037] An analysis module: used to conduct a multi-factor analysis on the battery aging process data set to obtain an evaluation result of the influence degree of different accelerated factors on the battery aging rate.

[0038] According to an accelerated factor evaluation system for affecting the aging of lithium-ion batteries provided by the present invention, the test monitoring module includes:

[0039] Test unit: used to perform an aging test on a lithium-ion battery under the test conditions;

[0040] Voltage sampling unit: used to perform high-frequency sampling on the terminal voltage of the battery during the aging test;

[0041] Current monitoring unit: used to continuously record the current value of the battery during the aging test;

[0042] Internal resistance measurement unit: used to detect the change in the internal resistance of the battery during the aging test.

[0043] An acceleration factor evaluation method and system for affecting the aging of lithium-ion batteries provided by the present invention, through the precise control and optimal combination of multiple acceleration factors, and combined with the comprehensive analysis of time dimension indicators, cycle dimension indicators and health state dimension indicators, establishes a quantitative evaluation system for the influence degree of acceleration factors, and for the first time realizes the precise quantification of the influence degree of single factor, double factor and triple factor combinations; in addition, it also greatly improves the efficiency of battery R & D and quality inspection; secondly, different from the traditional single acceleration factor method, the present invention ensures that the attenuation mechanism of the battery during the accelerated aging process is consistent with the actual use conditions through multi-factor comprehensive control, making the test results have higher reliability and predictive value; thirdly, the present invention also integrates all-round safety monitoring, and through multiple safety guarantee measures such as abnormal temperature detection, abnormal voltage detection and gas detection, effectively prevents the safety risks that may occur during the accelerated aging process, ensuring the safety and reliability of the test process. The test system and evaluation method of the present invention, through a multi-factor analysis model and a comprehensive evaluation algorithm, realize the intelligent control and analysis of the accelerated aging process, reduce human intervention, improve the accuracy and consistency of the test, and at the same time the present invention is applicable to various types and specifications of lithium-ion batteries and has a wide application prospect. Description of the Drawings

[0044] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings without creative efforts.

[0045] Figure 1 It is a schematic flowchart of an acceleration factor evaluation method for affecting the aging of lithium-ion batteries provided by an embodiment of the present invention;

[0046] Figure 2 It is a schematic structural diagram of an acceleration factor evaluation system for affecting the aging of lithium-ion batteries provided by an embodiment of the present invention.

[0047] Reference numerals:

[0048] 100, Parameter setting module; 200, Test monitoring module; 300, Analysis module;

[0049] 210, Test unit; 220, Voltage sampling unit; 230, Current monitoring unit; 240, Internal resistance measurement unit. Detailed implementation manners

[0050] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below with reference to the accompanying drawings in the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. They should not be construed as limiting the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present invention without creative efforts fall within the scope of protection of the present invention. In the description of the present invention, it should be understood that the terms used are only for the purpose of description and cannot be construed as indicating or implying relative importance.

[0051] The embodiments of the present invention will be described below with reference to the drawings.

[0052] As Figure 1 shown, the present invention provides a method for evaluating the acceleration factor affecting the aging of lithium-ion batteries, including:

[0053] S1: Set parameters for a variety of acceleration factors to obtain test conditions for different combinations of acceleration factors.

[0054] Among them, the acceleration factors in step S1 include: temperature, charge and discharge rate, SOC range.

[0055] In a specific embodiment, first, the temperature range selector selects a specific test temperature point between 25°C and 55°C according to the material characteristics and test requirements of the lithium-ion battery. For example, 25°C is selected as the room temperature reference point under standard test conditions, and 55°C is selected as the high-temperature acceleration point under accelerated aging conditions. After the temperature point is selected, the temperature control system uses precision temperature control equipment to maintain the test environment at the set temperature, controlling the temperature fluctuation range within ±0.5°C. At the same time, the temperature monitoring sensor continuously monitors the actual temperature, and the acquisition frequency is set to once every 30 seconds. The collected temperature data is compared with the set temperature to generate temperature fluctuation data. When a temperature deviation is detected, the feedback adjustment mechanism calculates the correction parameter according to the magnitude of the temperature deviation and automatically adjusts the output power of the heating or cooling device to ensure that the test environment temperature is accurately maintained near the set value.

[0056] For the charge-discharge rate acceleration factor, the rate setting range is controlled between 1C and 2C, where the 1C rate represents the current value at which the battery is fully charged or discharged within one hour. For example, for a lithium-ion battery with a capacity of 3000 mAh, the 1C charging current is 3A, and the 2C charging current is 6A. The charge-discharge rate setter allows the charging rate and the discharging rate to be set independently, forming various parameter combinations such as 1C / 1C, 2C / 2C, or 1C / 2C, etc. In actual tests, the accuracy of the charge-discharge current is controlled within ±0.5% of the set value to ensure the accurate implementation of the rate factor.

[0057] SOC (State of Charge) represents the ratio of the current capacity of the battery to the rated capacity. The SOC interval limiter sets the upper and lower limits of the battery charge and discharge to form different cycle intervals. Common settings include full-range cycling from 0 - 100% or limited-range cycling from 10 - 90%. It should be noted that to reduce the cumulative error in SOC calculation, the system performs a full charge-discharge calibration every 25 cycles to update the SOC reference value.

[0058] After setting different acceleration factors, the charge-discharge strategy generator constructs a battery cycle test execution plan based on the selected rate parameter combination and SOC parameter. The plan includes parameters such as the charge cut-off voltage, discharge cut-off voltage, constant current stage, constant voltage stage, current switching threshold, etc. For example, for a certain model of lithium battery, at a 1C charging rate, the charging strategy is set as: constant current charging to 4.2V, then constant voltage charging, and ending the charging when the charging current drops to 0.05C; the discharging strategy is set as: constant current discharging to 2.8V. The charge-discharge process controller precisely controls the battery cycle process according to the execution plan to ensure that each cycle strictly follows the preset conditions.

[0059] Among them, the combination methods of the different acceleration factor combinations in step S1 include:

[0060] Single-factor combination, and the single-factor combination includes temperature single-factor, charge-discharge rate single-factor, and SOC interval single-factor;

[0061] Two-factor combination, and the two-factor combination includes temperature and charge-discharge rate combination, temperature and SOC interval combination, and charge-discharge rate and SOC interval combination;

[0062] Three-factor combination, and the three-factor combination is the combination of temperature, charge-discharge rate, and SOC interval.

[0063] Further, for different combination methods of acceleration factors, the present invention designs three combination types: single-factor combination, two-factor combination, and three-factor combination. In the single-factor combination, two factors are maintained as the reference conditions, and only one factor is changed to the acceleration condition. For example, in the single-factor test of temperature, the temperature is set at 55°C, the charge-discharge rate is maintained at 1C, and the SOC range is maintained at 0-100%; in the single-factor test of charge-discharge rate, the rate is set at 2C, the temperature is maintained at 25°C, and the SOC range is maintained at 0-100%; in the single-factor test of SOC range, the range is limited to 10-90%, the temperature is maintained at 25°C, and the rate is maintained at 1C.

[0064] In the two-factor combination, two acceleration factors are simultaneously adjusted to the acceleration conditions, and the third factor is maintained as the reference condition. For the combination of temperature and charge-discharge rate, the temperature is set at 55°C, the rate is set at 2C, and the SOC range is maintained at 0-100%; for the combination of temperature and SOC range, the temperature is set at 55°C, the SOC range is limited to 10-90%, and the rate is maintained at 1C; for the combination of charge-discharge rate and SOC range, the rate is set at 2C, the SOC range is limited to 10-90%, and the temperature is maintained at 25°C.

[0065] In the three-factor combination, all three acceleration factors are simultaneously adjusted to the acceleration conditions, that is, the temperature is set at 55°C, the rate is set at 2C, and the SOC range is limited to 10-90%.

[0066] S2: Under the said test conditions, conduct an aging test on the lithium-ion battery and monitor it in real time to obtain a battery aging process data set.

[0067] Further, during the accelerated aging test of the lithium-ion battery, after determining the test conditions (including temperature, charge-discharge rate, and SOC range), in step S2, a high-precision data acquisition module comprehensively monitors and records the performance parameters of the lithium-ion battery under the set acceleration factor conditions, providing basic data support for subsequent data analysis.

[0068] Among them, step S2 further includes:

[0069] S21: Under the said test conditions, conduct an aging test on the lithium-ion battery to obtain a battery performance parameter data set.

[0070] In step S2, the battery needs to be pre-treated first. The pre-treatment includes performing 3 standard charge-discharge cycles on the battery to stabilize its performance, recording the initial capacity as the reference value. After the pre-treatment is completed, the battery will be placed in a specified temperature environment and subjected to a cycle test according to the set charge-discharge rate and SOC range.

[0071] Among them, step S21 specifically includes:

[0072] Perform high-frequency sampling on the terminal voltage of the battery during charge and discharge processes to obtain voltage change curve data.

[0073] Furthermore, in the present invention, data acquisition is performed by a high-precision voltage sampler with a sampling accuracy of ±0.1 mV. The voltage sampling frequency is dynamically adjusted according to the test stage: during the constant current charge and discharge stages, the sampling frequency is set to 1 Hz; at the end of the constant voltage charging stage and near the discharge cut-off point, the sampling frequency is increased to 10 Hz to capture the key information of rapid voltage changes. The collected original voltage data is processed by a digital filtering algorithm. The filtering algorithm uses a 5-point median filtering method, that is, the median of 5 consecutive sampling points is taken as the filtering result to effectively remove random noise. The filtered voltage data is stored according to the time series to form a voltage-time relationship curve.

[0074] Perform continuous recording on the current value of the battery during charge and discharge processes to obtain current change curve data.

[0075] Furthermore, in the present invention, a current monitoring device is adopted, specifically a combination of a Hall current sensor and a high-precision shunt. The measurement range is 0.01C. The current sampling frequency is synchronized with the voltage sampling to ensure the time consistency of current and voltage data. After the current data is collected, it is also processed by digital filtering. The sliding average filtering algorithm is used. The relationship between the filtered current data and time forms a current-time curve.

[0076] Perform regular detection on the internal resistance change of the battery during cycling to obtain internal resistance growth trend data.

[0077] Furthermore, the internal resistance measurement system uses two methods, the Hybrid Pulse Power Characterization (HPPC) method and the Electrochemical Impedance Spectroscopy (EIS) method, to measure the internal resistance. In the HPPC method, at a specific State of Charge (SOC) point, a 10-second constant current discharge pulse is applied, and the voltage difference before and after the pulse is divided by the pulse current to calculate the DC internal resistance. In the EIS method, at a specific SOC point, a small-signal sinusoidal AC excitation is applied to the battery, and the complex impedance of the battery is measured. The internal resistance measurement frequency is set to be performed once every 25 cycles. Before measurement, the battery needs to be static for 1 hour to reach a stable state. The internal resistance data is stored in the order of the number of cycles to form an internal resistance-number of cycles relationship curve, reflecting the change trend of the battery internal resistance with the number of cycles.

[0078] S22: Filter the noise and process the outliers in the battery performance parameter dataset to obtain the battery aging process dataset.

[0079] Specifically, it includes noise filtering and outlier processing. The originally collected voltage, current, and internal resistance data inevitably contain various noises, including random noise of measurement instruments, environmental electromagnetic interference, and fluctuations during signal transmission. Noise filtering is processed by combining multiple filtering algorithms. Outliers refer to data points that deviate from the normal range, usually caused by sensor failures, measurement errors, or environmental interference. For detected outliers, according to the continuity and physical meaning of the data, linear interpolation is used for processing. The linear interpolation method is based on the normal data points before and after the outlier, and calculates the estimated value of the outlier position by connecting with a straight line.

[0080] Among them, step S2 further includes:

[0081] S23: Real-time monitor the safety status of the lithium-ion battery during the accelerated aging test.

[0082] Furthermore, under accelerated conditions such as high temperature and high-rate charge and discharge of the lithium-ion battery, the safety risk increases significantly. Therefore, the present invention also sets up safety monitoring in step S23, which is also an important link during the test.

[0083] Among them, step S23 specifically includes:

[0084] Continuously monitor and process the surface temperature of the battery through a temperature anomaly detector to obtain a battery temperature anomaly warning signal;

[0085] Compare the upper and lower limits of the battery terminal voltage through a voltage anomaly detector to obtain a voltage overlimit warning signal;

[0086] Analyze the gas components in the battery surrounding environment in real time through a gas sensor to obtain a battery leakage or swelling warning signal;

[0087] Comprehensively judge and process the battery temperature anomaly warning signal, voltage overlimit warning signal, and battery leakage or swelling warning signal through a safety linkage control system to obtain a safety guarantee plan, and the safety guarantee plan includes emergency interruption of the test and degraded operation.

[0088] In a specific embodiment, for example, the temperature anomaly detector monitors that the surface temperature of the battery rapidly rises at the end of the 2C discharge, from 55°C (ambient temperature) to 58°C. Although it does not reach the first-level alarm threshold of 60°C, the temperature rise rate exceeds the dynamic threshold of 0.2°C / second. The system automatically increases the temperature acquisition frequency and extends the rest time after discharge, causing the battery temperature to fall back to the ambient temperature. The voltage anomaly detector monitors that during a certain cycle, due to a temporary failure of the charging controller, the charging voltage once rises to 4.23V, exceeding the upper threshold of 4.2V but not reaching the overcharge threshold of 4.25V. The system immediately adjusts the charging current to quickly bring the voltage back within the safe range. The gas sensor does not detect abnormal gas concentrations during the entire test process, the battery maintains good sealing performance, and there is no electrolyte leakage or gas emission. Based on the above monitoring data, the safety linkage control system calculates the comprehensive risk score to be 12 points, which is lower than the emergency handling threshold of 50 points. It continues to maintain the normal test process while increasing the monitoring frequency to ensure the safe progress of the test. Through the above multi-level and all-round safety monitoring mechanism, the accelerated aging test improves efficiency while ensuring the safety and reliability of the test process.

[0089] S3: Perform multi-factor analysis on the battery aging process dataset to obtain the evaluation result of the influence degree of different acceleration factors on the battery aging rate.

[0090] Among them, step S3 specifically includes:

[0091] Calculate the time used for the battery to complete the same number of cycles to obtain the aging rate index in the time dimension.

[0092] Count the number of cycles completed by the battery within the same time to obtain the aging rate index in the cycle dimension.

[0093] Calculate the number of cycles required for the battery to cycle to the same SOH value to obtain the aging rate index in the state of health dimension.

[0094] Furthermore, the aging rate index in the time dimension reflects the length of time required for the battery to complete a specific number of cycles under different acceleration factor conditions, directly characterizing the time efficiency of the aging test; the aging rate index in the cycle dimension reflects the number of cycles that the battery can complete within a fixed time period, characterizing the efficiency of the cycle test; the aging rate index in the state of health dimension reflects the number of cycles required for the battery capacity to decay to a specific health level.

[0095] Assign weights to the aging rate index in the time dimension, the aging rate index in the cycle dimension, and the aging rate index in the state of health dimension to obtain the comprehensive influence degree score of different acceleration factor combinations, and output the comprehensive influence degree score of different acceleration factor combinations as the evaluation result of the influence degree of different acceleration factors on the battery aging rate.

[0096] After obtaining the aging rate indicators in three dimensions, the indicators are weighted through a comprehensive evaluation algorithm, and the comprehensive influence degree scores of different combinations of acceleration factors are calculated. The analytic hierarchy process (AHP) is used for weight assignment to determine the relative importance of each indicator. Based on the purpose of the accelerated aging test, the indicator of the health state dimension is usually given the highest weight (0.6 in this embodiment), the indicator of the time dimension is the second (0.3 in this embodiment), and the indicator of the cycle dimension is the lowest (0.1 in this embodiment). The specific weight values can be adjusted according to the test requirements.

[0097] After obtaining the comprehensive influence degree scores of different combinations of acceleration factors, the individual and interactive effects of different acceleration factors are further analyzed. The single-factor influence analysis calculates the influence effect of each factor by comparing the score changes under the condition of changing a single factor. The two-factor interactive influence analysis evaluates the synergistic or antagonistic effect between factors by comparing the score differences between the two-factor combination and the single-factor superposition. The three-factor comprehensive influence analysis is directly based on the score results under the condition of the three-factor combination.

[0098] As Figure 2 shown, the present invention also provides an acceleration factor evaluation system for affecting the aging of lithium-ion batteries, including:

[0099] A parameter setting module 100: used to set parameters for a variety of acceleration factors to obtain test conditions for different combinations of acceleration factors.

[0100] A test monitoring module 200: used to conduct an aging test on the lithium-ion battery under the test conditions, and also used to monitor the aging test process in real time to obtain a battery aging process data set.

[0101] Among them, the test monitoring module 200 includes:

[0102] A test unit 210: used to conduct an aging test on the lithium-ion battery under the test conditions;

[0103] A voltage sampling unit 220: used to perform high-frequency sampling on the terminal voltage of the battery during the aging test;

[0104] A current monitoring unit 230: used to continuously record the current value of the battery during the aging test;

[0105] An internal resistance measurement unit 240: used to detect the change in the internal resistance of the battery during the aging test.

[0106] An analysis module: used to perform multi-factor analysis on the battery aging process data set to obtain an evaluation result of the influence degree of different acceleration factors on the battery aging rate.

[0107] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative work.

[0108] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0109] The following describes a method and system for evaluating an acceleration factor affecting the aging of lithium-ion batteries according to specific embodiments of the present invention.

[0110] Example 1: Under the conditions of room temperature (25 °C), charge and discharge current (1C / 1C), and SOC range (0 - 100%), a standard cycle aging test was carried out on a certain type of lithium-ion battery, and the capacity retention rate - cycle number - cycle time was recorded.

[0111] Example 2 (Single factor 1): Under the conditions of controlling the environmental temperature (55 °C), charge and discharge current (1C), and SOC range (0 - 100%), a standard cycle aging test was carried out on a certain type of lithium-ion battery, and the capacity retention rate - cycle number - cycle time was recorded.

[0112] Example 3 (Single factor 2): Under the conditions of room temperature (25 °C), charge and discharge current (2C / 2C), and SOC range (0 - 100%), a standard cycle aging test was carried out on a certain type of lithium-ion battery, and the capacity retention rate - cycle number - cycle time was recorded.

[0113] Example 4 (Single factor 3): Under the conditions of room temperature (25 °C), charge and discharge current (1C / 1C), and SOC range (10 - 90%), a standard cycle aging test was carried out on a certain type of lithium-ion battery, and the capacity retention rate - cycle number - cycle time was recorded.

[0114] Example 5 (Double Factor 1): Under the conditions of controlling the environmental temperature (55 °C), charge-discharge current (2C / 2C), and SOC range (0 - 100%), a standard cycle aging test was carried out on a certain type of lithium-ion battery, and the capacity retention rate - cycle number - cycle time was recorded.

[0115] Example 6 (Double Factor 2): Under the conditions of room temperature (25 °C), charge-discharge current (2C / 2C), and SOC range (10 - 90%), a standard cycle aging test was carried out on a certain type of lithium-ion battery, and the capacity retention rate - cycle number - cycle time was recorded.

[0116] Example 7 (Double Factor 3): Under the conditions of controlling the environmental temperature (55 °C), charge-discharge current (1C / 1C), and SOC range (10 - 90%), a standard cycle aging test was carried out on a certain type of lithium-ion battery, and the capacity retention rate - cycle number - cycle time was recorded.

[0117] Example 8 (Triple Factor): Under the conditions of controlling the environmental temperature (55 °C), charge-discharge current (2C / 2C), and SOC range (10 - 90%), a standard cycle aging test was carried out on a certain type of lithium-ion battery, and the capacity retention rate - cycle number - cycle time was recorded.

[0118] Through data analysis and evaluation, C (select 24 h), T (select 80 weeks), and Cs (select 90% SOH) were calculated to evaluate the influence degree of different acceleration factors on the battery aging process, providing data support for battery performance optimization. The specific evaluation results are shown in Table 1.

[0119] Table 1. Influence Degree of Different Acceleration Factors on Battery Aging Rate

[0120]

[0121] As shown in Table 1, taking the accelerated aging test of lithium-ion batteries as an example, Table 1 shows the specific implementation process of multi-factor analysis: Under eight test conditions, the aging test data of the battery were recorded. The standard condition (Example 1: 25 °C, 1C / 1C, 0 - 100% SOC) was used as a reference benchmark, and the other seven conditions were single-factor conditions (Examples 2 - 4), double-factor conditions (Examples 5 - 7), and triple-factor conditions (Example 8).

[0122] Calculation of the time dimension index T: The time required to complete 80 cycles under each condition was recorded. Under the standard condition, it took 12 days to complete 80 cycles (T1 = 12 days); under the triple-factor acceleration condition (55 °C, 2C / 2C, 10 - 90% SOC), it only took 7.13 days (T8 = 7.13 days). By calculating T1 / T8 = 1.68, it shows that the time efficiency under the triple-factor combination condition has increased by 68%.

[0123] Calculation of the cyclic dimension index C: Count the number of cycles completed within 24 hours under each condition. Under standard conditions, 7 cycles are completed in 24 hours (C1 = 7); under the three-factor acceleration condition, 11 cycles are completed in 24 hours (C8 = 11). By calculating C8 / C1 = 1.57, it shows that the cyclic efficiency under the three-factor combination condition has increased by 57%.

[0124] Calculation of the health state dimension index Cs: Calculate the number of cycles required for the battery capacity to decay to 90% SOH under each condition. Under standard conditions, the battery needs 700 cycles to decay to 90% SOH (Cs1 = 700); under the three-factor acceleration condition, only 432 cycles are required (Cs8 = 432). By calculating Cs1 / Cs8 = 1.62, it shows that the aging rate under the three-factor combination condition has accelerated by 62%.

[0125] Calculation of the comprehensive score: Assume that the weights of the three indicators are w1 = 0.3 (time dimension), w2 = 0.1 (cyclic dimension), and w3 = 0.6 (health state dimension) respectively. Then the score under standard conditions is the benchmark score of 100 points. For the three-factor acceleration condition: Score8 = 0.3×(12 / 7.13)+0.1×(11 / 7)+0.6×(700 / 432) = 0.3×1.68+0.1×1.57+0.6×1.62 = 0.504+0.157+0.972 = 1.633. Multiply the result by 100 and round to the nearest integer, and the comprehensive score of the three-factor combination is 163 points, indicating that the comprehensive acceleration effect has increased by 63%.

[0126] Calculate the comprehensive scores of other test conditions by a similar method. The scores for single-factor conditions are: 125 points for the temperature single factor (Example 2), 121 points for the charge-discharge rate single factor (Example 3), and 110 points for the SOC interval single factor (Example 4). This shows that among the single factors, temperature has the greatest impact on aging acceleration, followed by the charge-discharge rate, and the SOC interval has the least impact. The scores for two-factor conditions are: 145 points for the combination of temperature and charge-discharge rate (Example 5), 135 points for the combination of temperature and SOC interval (Example 6), and 130 points for the combination of charge-discharge rate and SOC interval (Example 7). This shows that among the two-factor combinations, the synergistic effect of temperature and charge-discharge rate is the most significant.

[0127] By comparing the impact degree scores of single factor, double factor and triple factor, it is found that the triple factor combination produces the strongest acceleration effect, and the score of the triple factor combination (163 points) is higher than the sum of any two single factor scores (such as the single factor of temperature 125 points plus the single factor of charge-discharge rate 121 points, with a total of 246 points), indicating that there is a complex interaction between the acceleration factors, rather than a simple linear superposition relationship. At the same time, by comparing the DVA curves (DV / DQ-Q) under different acceleration conditions, it is confirmed that the attenuation mechanism of the battery during the accelerated aging process is consistent with that under standard conditions, verifying the effectiveness of the accelerated test method.

[0128] The present invention provides a method and system for evaluating acceleration factors affecting the aging of lithium-ion batteries. By comprehensively considering and precisely controlling multiple acceleration factors, the comprehensiveness and accuracy of the test are significantly improved, providing important technical support for the research, development, production and application of lithium-ion batteries. It not only helps to optimize the battery design and improve the battery performance, but also has important economic and social values for extending the battery life, reducing the battery replacement frequency and lowering the usage cost.

[0129] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. An accelerated factor evaluation method for affecting the aging of lithium-ion batteries, characterized in that, Including: S1: Set parameters for multiple acceleration factors to obtain test conditions for different combinations of acceleration factors; S2: Under the said test conditions, conduct aging tests on lithium-ion batteries and monitor them in real time to obtain a battery aging process dataset; S3: Conduct multi-factor analysis on the battery aging process dataset to obtain an evaluation result of the influence degree of different acceleration factors on the battery aging rate.

2. The accelerated factor evaluation method for influencing the aging of a lithium-ion battery according to claim 1, wherein The acceleration factors in step S1 include: temperature, charge-discharge rate, and SOC range.

3. The accelerated factor evaluation method for influencing the aging of a lithium-ion battery according to claim 2, wherein The combination methods of the said different combinations of acceleration factors in step S1 include: Single-factor combination, and the single-factor combination includes temperature single-factor, charge-discharge rate single-factor, and SOC range single-factor; Two-factor combination, and the two-factor combination includes the combination of temperature and charge-discharge rate, the combination of temperature and SOC range, and the combination of charge-discharge rate and SOC range; Three-factor combination, and the three-factor combination is the combination of temperature, charge-discharge rate, and SOC range.

4. The accelerated factor evaluation method for influencing the aging of lithium-ion batteries according to claim 1, wherein Step S2 further includes: S21: Under the said test conditions, conduct aging tests on lithium-ion batteries to obtain a battery performance parameter dataset; S22: Conduct noise filtering and outlier processing on the battery performance parameter dataset to obtain a battery aging process dataset.

5. The accelerated factor evaluation method for influencing the aging of a lithium-ion battery according to claim 4, wherein Step S21 specifically includes: Conduct high-frequency sampling on the terminal voltage of the battery during charge and discharge to obtain voltage change curve data; Conduct continuous recording on the current value of the battery during charge and discharge to obtain current change curve data; Conduct regular detection on the internal resistance change of the battery during cycling to obtain internal resistance growth trend data.

6. The accelerated factor evaluation method for influencing the aging of lithium-ion batteries according to claim 1, characterized in that, Step S2 also includes: S23: Real-time monitor the safety status of lithium-ion batteries during the accelerated aging test process.

7. The accelerated factor evaluation method for influencing the aging of a lithium-ion battery according to claim 6, characterized in that, Step S23 specifically includes: Continuously monitor the surface temperature of the battery through a temperature anomaly detector to obtain a battery temperature anomaly warning signal; Compare the upper and lower limits of the battery terminal voltage through a voltage anomaly detector to obtain a voltage overlimit warning signal; Conduct real-time analysis on the gas components in the surrounding environment of the battery through a gas sensor to obtain a battery leakage or bulging warning signal; Conduct comprehensive judgment on the battery temperature anomaly warning signal, voltage overlimit warning signal, and battery leakage or bulging warning signal through a safety linkage control system to obtain a safety guarantee plan, and the safety guarantee plan includes test emergency interruption and degraded operation.

8. The accelerated factor evaluation method for affecting the aging of a lithium-ion battery according to claim 1, characterized in that Step S3 specifically includes: Calculate the time used for the battery to cycle the same number of weeks to obtain an aging rate index in the time dimension; Count the number of cycles completed by the battery within the same time to obtain an aging rate index in the cycle dimension; Calculate the number of cycles required for the battery to cycle to the same SOH value to obtain an aging rate index in the health state dimension; Assign weights to the aging rate index in the time dimension, the aging rate index in the cycle dimension, and the aging rate index in the health state dimension to obtain a comprehensive influence degree score for different combinations of acceleration factors, and output the comprehensive influence degree score of different combinations of acceleration factors as the evaluation result of the influence degree of different acceleration factors on the battery aging rate.

9. An accelerated factor evaluation system for affecting the aging of lithium-ion batteries, characterized in that, Including: Parameter setting module: used to set parameters for multiple acceleration factors to obtain test conditions with different combinations of acceleration factors; Test monitoring module: used to conduct an aging test on a lithium-ion battery under the test conditions, and also used to monitor the aging test process in real time to obtain a battery aging process data set; Analysis module: used to conduct a multi-factor analysis on the battery aging process data set to obtain an evaluation result of the influence degree of different acceleration factors on the battery aging rate.

10. The accelerated factor evaluation system for influencing the aging of lithium-ion batteries according to claim 9, wherein, The test monitoring module includes: Test unit: used to conduct an aging test on a lithium-ion battery under the test conditions; Voltage sampling unit: used to perform high-frequency sampling on the terminal voltage of the battery during the aging test; Current monitoring unit: used to continuously record the current value of the battery during the aging test; Internal resistance measurement unit: used to detect the change in the internal resistance of the battery during the aging test.

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